Simulation of ideal material blocks using cellular automata

We consider deterministic and probabilistic cellular automata to study and describe certain types of patterns in idealized material blocks. We have particular interest in patterns similar to fractures. The internal structure of these material blocks is assumed to be unknown and probabilistic cellular automata are used to obtain distributions for the referred internal structure. We consider the 1D case. Certain deterministic elementary rules are identified as elementary ideal fracture rules and the probabilistic rules are introduced as probabilistic interpolation of these elementary rules. The initial conditions are obtained from the visible borders of the surface (2D block). Therefore, each visible edge is giving additional information and a probabilistic fracture type pattern. Different methods to combine these patterns, into a final one, are discussed. Moreover, we introduce refinement techniques of the CA rules to improve the probabilities distributions. This refinement process may consider prescribed behaviour or empirical data, and, therefore, the CA rules behaviour becomes adjustable.